Send message to Authors

Paper short abstract

Based on ethnographic fieldwork, we develop “decentering AI” as a methodological strategy by highlighting the relations and worlds enacted through the production of AI, and those that produce AI. Decentering is a critical pathway to foreground the social, ecological and more-than-now in studying AI.

Paper long abstract

Contemporary studies of AI run up against its elusive character despite significant industry promises and optimism. The ontological boundaries of ‘AI proper’ are fuzzy, and the production and maintenance of these boundaries are protected by corporate interests. Consequently, critical AI research assuming to untangle these fuzzy boundaries may unwillingly contribute to the performance of AI as a coherent object and solution to myriad social and ecological problems (Suchman, 2023).

We suggest a research strategy of ‘decentering AI’ as an approach for Critical AI Studies. We build on work regarding methodological decentering to foreground causes of systemic discrimination instead of tweaking parameters (Gangadharan & Niklas, 2019); to attune to non-human relations and technological ‘un-making’ (Nicenboim et al., 2024); and to ‘study around’ multiple enacted objects (M’charek, 2000). We take seriously an ethnographic fieldwork observation in the Feminist Generative AI Lab: AI as an object of study easily disappears from view. For instance, when studying data work behind AI models pre-existing systems of labour exploitation take centre stage. Similarly, in research on the pollution of AI, decentering AI means recentering the toxic chemical relations between industries, ecologies and more-than-human lives.

Thus, decentering strategies do not ‘unmask’ AI but develop it as an object of methodological care. This contribution highlights how relations and worlds enacted through the production of AI come into view, alongside those that produce AI. This is one example of the critical in critical AI studies: decentering AI and foregrounding the social, ecological, and more-than-now.